Experimental investigation of discriminative parameter learning strategy on restrictive Bayesian networks
Bin Fu · Journal of Beijing Jiaotong University · 2011
To improve the classification accuracy by discriminative learning strategy,we analyze the performance of discriminative parameter learning strategy with different restrictive Bayesian networks.In this experiment,we build a new structure by deleting edges on a tree structure by partial derivatives of log conditional likelihood.The results show that the discriminative strategy runs well when the structure is simpler than the truth,and reduces performance when there are redundant edges.These results change the recognition that the redundant edges are irrelevant to classification performance.